In network communications, there is a phenomenon that harmful information is transmitted via a picture and multimedia video pictures. Therefore it is hoped to recognize this picture and multimedia video pictures. Here, the multimedia video pictures refer to a set of all pictures during a video display, which is a group of successive pictures. In order to recognize whether a picture or multimedia video pictures contain the harmful information, firstly the content of the picture and the multimedia video pictures need to be represented, then the picture and the multimedia video pictures are recognized by using a matching method, and at last, a corresponding monitoring measure is adopted according to the recognition result.
Currently, there are various feature-based picture representation methods using hash algorithm, and the hash algorithm here is also called hash function (or called hashing function, it has no influence on the essence of the present invention). The hash function is a function which is used to map an input message string of an arbitrary length into an output message string of a fixed length. The output message string is called hash value of the message, which is also called hashing value. The change of a single bit in any input message string will lead to a change of about half of the bits in the output message string. The hash function should at least meet the following conditions: 1) the length of the input message string is arbitrary; 2) the length of the output message string is fixed; 3) it is relatively easy to calculate the hash value of each given input message string; 4) if the description of the hash function is given, and two different input message strings mapped to one hash value are found, then the hash value cannot be calculated. Thus, the hash value can be used to represent a picture uniquely.
The current picture representation methods are mainly classified into two types. One type of method comprises the following steps: firstly a whole picture is represented by adopting the hash algorithm, and then recognized. The other type of method comprises the following steps: firstly a picture is divided in a certain manner, then the hash value of each divided part is calculated to obtain a group of hash values for representing the picture, and at last, the picture is recognized through each hash value; and this method can recognize a picture of which the content is modified.
For the two types of method, the first type of method can only be used to recognize an identical picture, but can not be used to recognize a modified picture; while the second type of method can recognize a content-modified picture, however, it is required to carry out a matching on each hash value during recognizing a picture. Therefore the shortcomings of the two types of picture representation method can both lead to inefficient picture recognition, so that the two types of picture representation method cannot be applied to a monitoring system conveniently. Particularly, if the two types of method are combined together, i.e. firstly using the first type of method and then the second type of method, then there are still some shortcomings in efficiency (i.e. the is efficiency is low) because hash calculation should be executed once for the picture and binary bytes for representing the initial picture are too many. Such shortcomings also exist with respect to the multimedia video pictures.